pandas Working with Time Series Partial String Indexing
Example
A very handy way to subset Time Series is to use partial string indexing. It permits to select range of dates with a clear syntax.
Getting Data
We are using the dataset in the Creating Time Series example
Displaying head and tail to see the boundaries
se.head(2).append(se.tail(2))
# 2016-09-24 44
# 2016-09-25 47
# 2016-12-31 85
# 2017-01-01 48
Subsetting
Now we can subset by year, month, day very intuitively.
By year
se['2017']
# 2017-01-01 48
By month
se['2017-01']
# 2017-01-01 48
By day
se['2017-01-01']
# 48
With a range of year, month, day according to your needs.
se['2016-12-31':'2017-01-01']
# 2016-12-31 85
# 2017-01-01 48
pandas also provides a dedicated truncate function for this usage through the after and before parameters -- but I think it's less clear.
se.truncate(before='2017')
# 2017-01-01 48
se.truncate(before='2016-12-30', after='2016-12-31')
# 2016-12-30 13
# 2016-12-31 85
